Multi-atlas segmentation using clustering, local non-linear manifold embeddings and target-specific templates

Multi-atlas segmentation (MAS) has become an established technique for the automated delineation of anatomical structures. The often manually annotated labels from each of multiple pre-segmented images (atlases) are typically transferred to a target through the spatial mapping of corresponding structures of interest. The mapping can be estimated by pairwise registration between each atlas and the target or by creating an intermediate population template for spatial normalisation of atlases and targets. The former is done at runtime which is computationally expensive but provides high accuracy. In the latter approach the template can be constructed from the atlases offline requiring only one registration to the target at runtime. Although this is computationally more efficient, the composition of deformation fields can lead to decreased accuracy. Our goal was to develop a MAS method which was both efficient and accurate. In our approach we create a target-specific template (TST) which has a high similarity to the target and serves as intermediate step to increase registration accuracy. The TST is constructed from the atlas images that are most similar to the target. These images are determined in low-dimensional manifold spaces on the basis of deformation fields in local regions of interest. We also introduce a clustering approach to divide atlas labels into meaningful sub-regions of interest and increase local specificity for TST construction and label fusion. Our approach was tested on a variety of MR brain datasets and applied to an in-house dataset. We achieve state-of-the-art accuracy while being computationally much more efficient than competing methods. This efficiency opens the door to the use of larger sets of atlases which could lead to further improvement in segmentation accuracy

Multi-atlas segmentation using clustering, local non-linear manifold embeddings and target-specific templates

Multi-atlas segmentation (MAS) has become an established technique for the automated delineation of anatomical structures. The often manually annotated labels from each of multiple pre-segmented images (atlases) are typically transferred to a target through the spatial mapping of corresponding structures of interest. The mapping can be estimated by pairwise registration between each atlas and the target or by creating an intermediate population template for spatial normalisation of atlases and targets. The former is done at runtime which is computationally expensive but provides high accuracy. In the latter approach the template can be constructed from the atlases offline requiring only one registration to the target at runtime. Although this is computationally more efficient, the composition of deformation fields can lead to decreased accuracy. Our goal was to develop a MAS method which was both efficient and accurate. In our approach we create a target-specific template (TST) which has a high similarity to the target and serves as intermediate step to increase registration accuracy. The TST is constructed from the atlas images that are most similar to the target. These images are determined in low-dimensional manifold spaces on the basis of deformation fields in local regions of interest. We also introduce a clustering approach to divide atlas labels into meaningful sub-regions of interest and increase local specificity for TST construction and label fusion. Our approach was tested on a variety of MR brain datasets and applied to an in-house dataset. We achieve state-of-the-art accuracy while being computationally much more efficient than competing methods. This efficiency opens the door to the use of larger sets of atlases which could lead to further improvement in segmentation accuracy

SARS-CoV-2 is associated with changes in brain structure in UK Biobank

There is strong evidence of brain-related abnormalities in COVID-191,2,3,4,5,6,7,8,9,10,11,12,13. However, it remains unknown whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here we investigated brain changes in 785 participants of UK Biobank (aged 51–81 years) who were imaged twice using magnetic resonance imaging, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans—with 141 days on average separating their diagnosis and the second scan—as well as 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including (1) a greater reduction in grey matter thickness and tissue contrast in the orbitofrontal cortex and parahippocampal gyrus; (2) greater changes in markers of tissue damage in regions that are functionally connected to the primary olfactory cortex; and (3) a greater reduction in global brain size in the SARS-CoV-2 cases. The participants who were infected with SARS-CoV-2 also showed on average a greater cognitive decline between the two time points. Importantly, these imaging and cognitive longitudinal effects were still observed after excluding the 15 patients who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease through olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious effect can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow-up

Assessing the impact of posture on diaphragm morphology and function using an open upright MRI system – a pilot study

PurposeThe diaphragm is the most important muscle of respiration. Disorders of the diaphragm can have a deleterious impact on respiratory function. We aimed to evaluate the use of an open-configuration upright low-field MRI system to assess diaphragm morphology and function in patients with bilateral diaphragm weakness (BDW) and chronic obstructive pulmonary disease (COPD) with hyperinflation.MethodThe study was approved by the National Research Ethics Committee, and written consent was obtained. We recruited 20 healthy adult volunteers, six subjects with BDW, and five subjects with COPD with hyperinflation. We measured their vital capacity in the upright and supine position, after which they were scanned on the 0.5 T MRI system during 10-second breath-holds at end-expiration and end-inspiration in both positions. We developed and applied image analysis methods to measure the volume under the dome, maximum excursion of hemidiaphragms, and anterior-posterior and left-right extension of the diaphragm.ResultsAll participants were able to complete the scanning protocol. The patients found scanning in the upright position more comfortable than the supine position. All differences in the supine inspiratory-expiratory parameters, excluding left-right extension, were significantly smaller in the BDW and COPD groups compared with healthy volunteers. No significant correlation was found between the postural change in diaphragm morphology and vital capacity in either group.ConclusionOur combined upright-supine MR imaging approach facilitates the assessment of the impact of posture on diaphragm morphology and function in patients with BDW and those with COPD with hyperinflation

Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study.

Funder: National Institute for Health Research (NIHR)INTRODUCTION: Magnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King's College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data. CONCLUSION: These results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study

Photography-based taxonomy is inadequate, unnecessary, and potentially harmful for biological sciences

The question whether taxonomic descriptions naming new animal species without type specimen(s) deposited in collections should be accepted for publication by scientific journals and allowed by the Code has already been discussed in Zootaxa (Dubois & Nemésio 2007; Donegan 2008, 2009; Nemésio 2009a–b; Dubois 2009; Gentile & Snell 2009; Minelli 2009; Cianferoni & Bartolozzi 2016; Amorim et al. 2016). This question was again raised in a letter supported by 35 signatories published in the journal Nature (Pape et al. 2016) on 15 September 2016. On 25 September 2016, the following rebuttal (strictly limited to 300 words as per the editorial rules of Nature) was submitted to Nature, which on 18 October 2016 refused to publish it. As we think this problem is a very important one for zoological taxonomy, this text is published here exactly as submitted to Nature, followed by the list of the 493 taxonomists and collection-based researchers who signed it in the short time span from 20 September to 6 October 2016

Medium-term effects of SARS-CoV-2 infection on multiple vital organs, exercise capacity, cognition, quality of life and mental health, post-hospital discharge.

BACKGROUND: The medium-term effects of Coronavirus disease (COVID-19) on organ health, exercise capacity, cognition, quality of life and mental health are poorly understood. METHODS: Fifty-eight COVID-19 patients post-hospital discharge and 30 age, sex, body mass index comorbidity-matched controls were enrolled for multiorgan (brain, lungs, heart, liver and kidneys) magnetic resonance imaging (MRI), spirometry, six-minute walk test, cardiopulmonary exercise test (CPET), quality of life, cognitive and mental health assessments. FINDINGS: At 2-3 months from disease-onset, 64% of patients experienced breathlessness and 55% reported fatigue. On MRI, abnormalities were seen in lungs (60%), heart (26%), liver (10%) and kidneys (29%). Patients exhibited changes in the thalamus, posterior thalamic radiations and sagittal stratum on brain MRI and demonstrated impaired cognitive performance, specifically in the executive and visuospatial domains. Exercise tolerance (maximal oxygen consumption and ventilatory efficiency on CPET) and six-minute walk distance were significantly reduced. The extent of extra-pulmonary MRI abnormalities and exercise intolerance correlated with serum markers of inflammation and acute illness severity. Patients had a higher burden of self-reported symptoms of depression and experienced significant impairment in all domains of quality of life compared to controls (p<0.0001 to 0.044). INTERPRETATION: A significant proportion of patients discharged from hospital reported symptoms of breathlessness, fatigue, depression and had limited exercise capacity. Persistent lung and extra-pulmonary organ MRI findings are common in patients and linked to inflammation and severity of acute illness. FUNDING: NIHR Oxford and Oxford Health Biomedical Research Centres, British Heart Foundation Centre for Research Excellence, UKRI, Wellcome Trust, British Heart Foundation

Data from: How diverse is Mitopus morio? Integrative taxonomy detects cryptic species in a small-scale sample of a widespread harvestman

Mitopus morio is a widespread harvestman species occurring in most of Europe and in moderate and cold-moderate zones of Asia and North America. The species is characterized by extreme variability in body size and leg length. As leg length is correlated with habitat temperature, M. morio has been considered as an example of Allen's rule. Recently, observations for a single location in Tyrol, Austria, indicated the absence of mating between short- and long-legged individuals. This study examines for signs of putative cryptic species in M. morio using an integrative approach that combines mating trials, amplified fragment length polymorphism whole-genome scans, mitochondrial sequences and morphometrics. The mating trials did not corroborate the initial hypothesis of a reproductive barrier associated with leg size. Both types of genetic data revealed the existence of three distinct groups, in line with the mating results but largely unrelated to leg morphology and geographical origin of specimens. Morphometric characters supporting the findings of the other disciplines were identified using a supervised approach. We infer from all data together the existence of strongly diverged cryptic lineages among the analysed individuals, cautiously interpret them as three sympatric species and conclude that in these harvestmen Allen's rule applies at different levels. Due to the unexpected amount of differentiation found within a geographical scale very small compared with the distribution of M. morio, we suggest a thorough revision of the genus prior to formal taxonomic changes. Our case study underlines the general applicability of the integrative taxonomic protocol used and highlights the relevance of several rationales implemented in the protocol

Bioclimatic variables used for ENMs

19 bioclimatic variables for current conditions, Last Glacial Maximum and mid-Holocene (MIROC and CCSM models), extracted from the Wordclim database for the study region (European Alps). Additionally, elevation data and the "surface area" variable are included (see Materials and Methods for more details)

Data from: Glacial refugia, recolonisation patterns, and diversification forces in Alpine-endemic Megabunus harvestmen

The Pleistocene climatic fluctuations had a huge impact on all life-forms, and various hypotheses regarding the survival of organisms during glacial periods have been postulated. In the European Alps, evidence has been found in support of refugia outside the ice shield (massifs de refuge) acting as sources for postglacial recolonisation of inner-Alpine areas. In contrast, evidence for survival on nunataks, ice-free areas above the glacier, remains scarce. Here, we combine multivariate genetic analyses with ecological niche models (ENMs) through multiple timescales to elucidate the history of alpine Megabunus harvestmen throughout the ice ages, a genus that comprises eight high altitude endemics. ENMs suggest two types of refugia throughout the Last Glacial Maximum, inner-Alpine survival on nunataks for four species and peripheral refugia for further four species. In some geographic regions, the patterns of genetic variation are consistent with long-distance dispersal out of massifs de refuge, repeatedly coupled with geographic parthenogenesis. In other regions, long-term persistence in nunataks may dominate the patterns of genetic divergence. Overall, our results suggest that glacial cycles contributed to allopatric diversification in Alpine Megabunus, both within and at the margins of the ice shield. These findings exemplify the power of ENM projections coupled with genetic analyses to identify hypotheses about the position and number of glacial refugia and thus to evaluate the role of Pleistocene glaciations in driving species-specific responses of recolonisation or persistence that may have contributed to observed patterns of biodiversity